Three-dimensional geometrical feature estimation for ship classification through SAR images

C. Duan, W. Hu, Xiaoyong Du
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引用次数: 1

Abstract

For the purpose of ship classification with SAR images, we put forward a way to extract the three-dimensional geometrical features of the ship in the case when the extracting and matching of the ship scattering centers are handicapped by the ocean movement and the scintillation of SAR images. An ellipsoid-ellipse model is used to approximate the ship and its SAR silhouette. With this model, the radar azimuths and the ship length are estimated in an almost unbiased way. Moreover, by introducing the length-width joint probability density function based on real samples, we got the width and height estimation by solving a constrained nonlinear Least Square problem. The estimations show satisfactory accuracy and robustness for the classification. The electromagnetic simulated images are used to validate the feasibility of the ellipsoid-ellipse model, as well as the efficiency of the algorithm.
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基于SAR图像的船舶入级三维几何特征估计
为了利用SAR图像进行船舶分类,针对船舶散射中心的提取和匹配受海洋运动和SAR图像闪烁影响的情况,提出了一种提取船舶三维几何特征的方法。采用椭球-椭圆模型逼近舰船及其SAR轮廓。利用该模型,对雷达方位角和船长进行了几乎无偏的估计。在此基础上,引入基于实际样本的长-宽联合概率密度函数,通过求解约束非线性最小二乘问题得到宽度和高度的估计。结果表明,该方法具有较好的分类精度和鲁棒性。利用电磁仿真图像验证了椭球-椭圆模型的可行性和算法的有效性。
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